摘要
针对建筑修复基于点云边缘检测的墙面裂缝提取结果受可变阈值和裂缝形态影响严重的问题,提出一种结合裂缝点云的几何特征和二维分布特征,联合共享顶点Delaunay三角形网格与邻近异常点二次判断的墙面裂缝检测方法:(1)基于平面拟合和三维坐标变换实现点云数据降维;(2)利用Delaunay三角形网格质量特征排除裂缝处格网并结合点云几何特征和分布特征实现内外层异常点二次判断;(3)通过密度聚类实现裂缝区域的精确筛选,并将裂缝边缘点还原到三维空间提取裂缝的几何特征上。通过建筑墙面激光点云数据进行实验验证与分析,实验结果表明:实测墙面的裂缝检测召回率、准确率均达到100%,与人工提取结果相比较,裂缝几何特征的最大相对偏差为-9.7%。该方法可为大规模建筑墙面损坏检测提供技术支撑。
In response to the difficult problem of wall crack detection,which is one of the important tasks in building restoration,previous crack extraction techniques based on point cloud edge detection were severely affected by variable thresholds and crack morphology.This paper proposes a wall crack detection method that combines the geometric and two-dimensional distribution characteristics of crack point clouds,and combines the Delaunay triangular mesh of shared vertices with adjacent abnormal points for secondary judgment.Firstly,point cloud data dimensionality reduction is achieved based on plane fitting and 3D coordinate transformation;Then,the Delaunay triangle mesh quality features are used to exclude the grid at the crack location,and combined with the geometric and distribution characteristics of the point cloud,a secondary judgment of the inner and outer abnormal points is achieved;Finally,precise screening of crack areas is achieved through density clustering,and the edge points of cracks are restored to the three-dimensional space to extract the geometric features of cracks.Experimental verification and analysis were conducted using laser point cloud data on building walls.The results showed that the recall and accuracy of crack detection on the measured walls reached 1oo%.Compared with the manually extracted results,the maximum relative deviation of the geometric features of cracks was-9.7%.This method can provide technical support for large-scale wall damage detection in buildings.
作者
杨烨
沈月千
YANG Ye;SHEN Yueqian(College of Earth Sciences and Engineering,Hohai University,Nanjing 21l100,China)
出处
《测绘科学》
CSCD
北大核心
2024年第3期98-107,共10页
Science of Surveying and Mapping
关键词
遥感
激光点云
裂缝提取
Delaunay网格
点云特征提取
remote sensing
laser point clouds
crack extraction
Delaunay grid
point cloud feature extraction
